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Mastering Image Segmentation with PyTorch
Learn practical image segmentation using PyTorch. Master CNNs, semantic segmentation, and deep learning techniques for real-world applications.
Course Cost
₹ 2,699
Beginner
Skill Level
6 Hours
Self-paced lessons
This comprehensive course offers a deep dive into image segmentation using PyTorch, combining theoretical foundations with hands-on implementation. Starting with essential concepts, students progress through PyTorch basics, CNNs, and advanced semantic segmentation techniques. The curriculum emphasizes practical application, featuring real-world projects and industry-standard evaluation metrics. Led by experts, the course covers everything from data preparation to model architecture, making complex segmentation tasks accessible to both beginners and experienced practitioners. The hands-on approach ensures students can confidently implement these techniques in real-world scenarios.
English
What you'll learn
Apply multi-class semantic segmentation using PyTorch to real-world datasets
Analyze UNet and FPN model architectures for effective image segmentation
Implement and optimize deep learning models with appropriate loss functions
Master CNN architecture and layer calculations for image analysis
Develop practical skills in data preparation and preprocessing
Evaluate model performance using industry-standard metrics
Skills you'll gain
This course includes:
303 Minutes PreRecorded video
1 assignment
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course covers the fundamentals and advanced techniques of image segmentation using PyTorch. Students begin with PyTorch basics and tensor operations before progressing to convolutional neural networks (CNNs) and semantic segmentation. The curriculum includes hands-on coding sessions for data preparation, model building, and evaluation. Key topics include CNN architecture, upsampling methods, loss functions, and performance metrics. The course emphasizes practical implementation through real-world projects and industry-standard evaluation techniques.
Course Overview and Setup
Module 1 · 35 Minutes to complete
PyTorch Introduction (Refresher)
Module 2 · 1 Hours to complete
Convolutional Neural Networks (Refresher)
Module 3 · 49 Minutes to complete
Semantic Segmentation
Module 4 · 2 Hours to complete
Fee Structure
Payment options
Financial Aid
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
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Frequently asked Questions
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